In this study, the authors investigate the role of advertising in affecting the extent of bias in the media. When making advertising choices, advertisers evaluate both the size and the composition of the readership of the different outlets. The profile of the readers matters since advertisers wish to target readers who are likely to be receptive to their advertising messages. It is demonstratedthat when advertising supplements subscription fees, it may serve as a polarizing or moderating force, contingent upon the extent of heterogeneity among advertisers. When heterogeneity is large, each advertiser chooses a single outlet for placing ads (Single-Homing), and greater polarization arises in comparison to the case that media relies on subscription fees only for revenues. In contrast, when heterogeneity is small, each advertiser chooses to place ads in multiple outlets (Multi-Homing), and reduced polarization results. For intermediate levels of heterogeneity, some advertisers choose to Single-Home and others choose to Multi-Home.
In this study, we investigate a newspaper’s decision to expand its product line by adding an online edition that incorporates user-generated content, and the impact of this decision on its slanting of news. We demonstrate that adding an online edition results in reduced profits for competing newspapers in comparison to an environment in which they offer only print editions. However, at the equilibrium, each newspaper offers the online version in order to avoid losing market share to rivals. The results also show the mitigating effect of such a product line extension on the extent of bias in print media.
This article reports on a marketing initiative at a pharmaceutical company to redesign its distribution network. Distribution affects a firm’s cost and customer satisfaction and drives profitability. Using a nonlinear mixed-integer programming model, the authors develop a distribution network with a dual emphasis on minimizing the total distribution costs and improving the customer service levels. Specifically, they address the following issues: They (1) determine the optimal number of regional distribution centers the firm should operate with, (2) identify where in the United States the firm should locate these distribution centers, (3) allocate each retailer/customer distribution center to an appropriate regional distribution center, and (4) determine the total transportation costs and service level for each case. Finally, they conduct a sensitivity analysis to determine the impact of changes in problem parameters on the optimality of the proposed model. This marketing initiative at the studied firm reduced the total distribution costs by $1.99 million (6%) per year, while increasing the customer on-time delivery from 61.41% to 86.2%, an improvement of 40.4%.